code: def test_create_train_X_y_output_when_y_is_series_10_and_exog_is_dataframe_of_bool_str(
      v_exog_1, v_exog_2, dtype
  ):
      """
      Test the output of create_train_X_y when y=pd.Series(np.arange(10)) and
      exog is a pandas dataframe with two columns of bool or str.
      """
      y = pd.Series(np.arange(10), dtype=float)
      exog = pd.DataFrame(
          {
              "exog_1": v_exog_1 * 10,
              "exog_2": v_exog_2 * 10,
          }
      )
      forecaster = ForecasterAutoreg(LinearRegression(), lags=5)
      results = forecaster.create_train_X_y(y=y, exog=exog)
      expected = (
          pd.DataFrame(
              data=np.array(
                  [
                      [4.0, 3.0, 2.0, 1.0, 0.0],
                      [5.0, 4.0, 3.0, 2.0, 1.0],
                      [6.0, 5.0, 4.0, 3.0, 2.0],
                      [7.0, 6.0, 5.0, 4.0, 3.0],
                      [8.0, 7.0, 6.0, 5.0, 4.0],
                  ]
              ),
              index=pd.RangeIndex(start=5, stop=10, step=1),
              columns=["lag_1", "lag_2", "lag_3", "lag_4", "lag_5"],
          )
          .assign(exog_1=v_exog_1 * 5, exog_2=v_exog_2 * 5)
          .astype({"exog_1": dtype, "exog_2": dtype}),
          pd.Series(
              data=np.array([5, 6, 7, 8, 9]),
              index=pd.RangeIndex(start=5, stop=10, step=1),
              name="y",
              dtype=float,
          ),
      )
  
      pd.testing.assert_frame_equal(results[0], expected[0])
      pd.testing.assert_series_equal(results[1], expected[1])
  
imports: import re
  import pytest
  import numpy
  import pandas
  from skforecast.ForecasterAutoreg import ForecasterAutoreg
  from skforecast.preprocessing import TimeSeriesDifferentiator
  from skforecast.exceptions import MissingValuesExogWarning
  from sklearn.linear_model import LinearRegression
  from sklearn.compose import ColumnTransformer
  from sklearn.preprocessing import StandardScaler
  from sklearn.preprocessing import OneHotEncoder
  from .fixtures_ForecasterAutoreg import data
label_desc: Use image node_id 10 for calling a global function with example usage: test_create_train_X_y_output_when_y_is_series_10_and_exog_is_dataframe_of_bool_str(v_exog_1, v_exog_2, dtype) without return types